Title :
Potholes Detection Based on SVM in the Pavement Distress Image
Author :
Lin, Jin ; Liu, Yayu
Author_Institution :
Coll. of Math. & Comput. Sci., Fuzhou Univ., Fuzhou, China
Abstract :
There are much more researches on the recognition of the cracks on the distress pavement, but the research on the potholes is relatively less. In this paper, Texture measure based on the histogram is extracted as the features of the image region, and the non-linear support vector machine is built up to identify whether a target region is a pothole. Based on this, an algorithm for recognizing the potholes of the pavement is proposed. The experimental results show that the algorithm can achieve a high recognition rate.
Keywords :
image recognition; image texture; roads; structural engineering computing; support vector machines; SVM; histogram; image features; image recognition; pavement distress image; potholes detection; support vector machine; Classification algorithms; Feature extraction; Image recognition; Image segmentation; Pixel; Support vector machines; Training; Pavement Potholes; Support Vector Machine (SVM); image recognition;
Conference_Titel :
Distributed Computing and Applications to Business Engineering and Science (DCABES), 2010 Ninth International Symposium on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-7539-1
DOI :
10.1109/DCABES.2010.115
